Time Series Analysis and Forecast

This is a series of notebooks to support lectures on Time series analysis and forecast for a course I will be giving for DeepLearning Italia.

This is part of a series of other lectures modules on

1. Introduction to Data Science 🧮
2. Statistical Learning 📈
3. Deep Learning 🦾
4. Computer Vision Hands-On 🕶️
5. Recommender Systems 🚀

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Content of Lectures

0. Statistics Review 📈
1. Pandas for Time Series Analysis 📊
2. Time Series and Visualisation tools 🖍️
3. Time Series manipulations and operations 🧮
4. Time Series decomposition 🔪
5. Time Series forecast I 🔭
6. Time Series forecast II 🕸️
7. Time Series forecast III 🕷️️
8. Time Series with Transformers 🤖
9. Time Series with Transformers 🎯

Bonus: you can find a pdf of the slides I used in the course here.

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Install requirements

As usual, it is advisable to create a virtual environment to isolate dependencies. One can follow this guide and the suitable section according to the OS.

Once the virtual environment has been set up, one has to run the following instruction from a command line

pip install -r requirements.txt

This installs all the packages the code in this repository needs.

Interact with notebooks

You can use Binder, to interact with notebooks and play with the code and the exercises.

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Your lecturer

Oscar de Felice

I am a theoretical physicist, a passionate programmer and an AI curious.

I write medium articles (with very little amount of regularity), you can read them here. I also have a github profile where I store my personal open-source projects.

📫 Reach me!

Buy me a coffee

If you like these lectures, consider to buy me a coffee ☕️ or a slice of pizza 🍕!